Sentiment classification is significant in everyday life of everyone, in political activities, activities of commodity production, commercial activities. In this research, we propose a new model for Big Data sentiment classification in the parallel network environment. Our new model uses STING Algorithm (SA) (in the data mining field) for English document-level sentiment classification with Hadoop Map (M)/Reduce (R) based on the 90,000 English sentences of the training data set in a Cloudera parallel network environment — a distributed system. In the world there is not any scientific study which is similar to this survey. Our new model can classify sentiment of millions of English documents with the shortest execution time in the parallel network environment. We test our new model on the 25,000 English documents of the testing data set and achieved on 61.2% accuracy. Our English training data set includes 45,000 positive English sentences and 45,000 negative English sentences.
The aim of following study was to examine the relationship between energy consumption and economic growth in Indonesia. This study has used quantitative research design for assessing the energy consumption and its link with economic growth in Indonesia for the period of 2000-2019. The independent variable in this study was energy consumption whereas; dependent variable was economic growth in Indonesia .The data is analysed through E-views using autoregressive distributed lag co-integration approach for long-run relationship, and long-run and short-run coefficients, Augmented Dickey Fuller and Johansen co-integration. The findings have revealed that economic growth and energy consumption has association with each other. Within the given historic data, energy consumption has the ability to predict economic growth in Indonesia. The research can be improved through increasing sample size, number of variables and countries for comparison. This study also provides the guideline to the polcymakers that they should develop the policies related to the energy consumption that enhance the economic growth of the country.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.